Use of the Internet by the general public is gaining popularity. More and more people are getting access to the Internet and the vast amount of information that it provides. Along with the rapid increase in the number of Internet users, advertising on the Internet has consequently become an important priority for many advertisers.
As a result, for web portals and ISPs, a significant amount of revenue is generated from displaying advertisers' ad banners on web sites or web pages. For example, for a preeminent portal such as Yahoo!® which is visited daily by hundreds of thousands, if not millions of users, considerable revenue is generated by displaying an advertiser's advertisements on its web sites or web pages.
For web portals like Yahoo!, advertisers generally pay a fee for each advertisement viewed by web users. Contracts to present advertisements are normally signed well in advance of delivery, from several weeks to months. The duration of contracts ranges from one day to multiple years. Typically, there are several types of contracts, including regular contracts, exclusive contracts and non-exclusive contracts. For regular contracts, the advertisers purchase a designated number of ad views on a chosen space (web page). A type of regular contract is based upon the CPM (i.e., cost per thousand impressions or views) generally linked to, for example, a specific web page or search term. Under a CPM arrangement involving a search engine, a particular advertisement will have a set cost corresponding to a guaranteed number of times (per 1,000 matches or views) a term is searched during a period of time. For exclusive contracts, advertisers purchase all the ad views on a chosen web page or search term. A type of exclusive contract might be a CPM contract excluding all other advertisers from using a specific search term or sequence of search terms.
For non-exclusive contracts, the advertiser purchases leftover ad views on a chosen space not reserved under an exclusive contract after other regular contracts related to that space have been fulfilled. Such advertisements, referred to herein as “run of network” ads, are generally displayed “out-of-context.” An advertisement is out-of-context if it is displayed on a space or web page unrelated to the subject matter of the advertisement. Run of network ads are less desirable from an advertiser's viewpoint because users generally are less likely to respond to advertisements that are unrelated to a user's interest in the particular space. Consequently, run of network ads command a lower price, and thus generate less revenue than advertisements based upon regular and exclusive contracts.
Like advertising delivered through more traditional media, such as TV or printed publications, advertising on the Internet is similarly subject to physical and temporal limitations. For obvious reasons, it is a natural and often most selected choice for advertisers to request ad views on the more relevant web pages for maximum exposure to a targeted audience. However, since there is a finite amount of physical space on a web page, demand for ad space or ad views on relevant web pages often exceeds supply. If such demand cannot be serviced (i.e., advertisements cannot be displayed according to the advertiser's wishes), then revenue otherwise derived therefrom will not be realized.
For web portals, like Yahoo!, advertisements are displayed on web pages resulting from a user-defined search based upon one or more search terms. Generally, there are more advertisers interested in targeting their advertisements based on frequently used search terms than there is room or means to accommodate such advertisements. For example, in an exclusive contract, an advertiser of baby books has rights to all occurrences, each, of one or more keywords associated with a user's search, such as “books” and/or “baby.” Other advertisers of books, however, will have no opportunity to key their respective advertisements to the term “books” and thus may have only the less favorable run of network ads as a consideration.
A common approach to improving the effectiveness of presenting targeted advertisements to those users interested in receiving product information from various sellers is to employ demographic characteristics (i.e., age, income, sex, occupation, etc.) for predicting the behavior of groups of different users. Advertisements then will be presented to each user in a targeted audience based upon predicted behaviors rather than in response to certain keyword search terms.
This approach, however, has significant drawbacks. Since users generally declare their demographics upon registering for an email or My Yahoo! account, for example, users sometime provide inaccurate information about their demographics, such as claiming to be female rather than male. Another disadvantage of demographic ad targeting is that there are underlying assumptions that are not necessarily accurate. For example, advertisers might presume that if one is a doctor, then that person would be interested in golf. The effectiveness of demographic ad targeting is thus impaired by the assumptions in which it is based upon.
Another convention approach is profile-based ad targeting. In this approach, user profiles specific to each of the users are generated to model user behavior, for example, by tracking each user's path through a web site or network of sites, and then compiling a profile based on what pages and advertisements were delivered to the user. Using aggregated data, a correlation develops between users in a certain target audience and the products that those users purchase. The correlation then is used to target potential purchasers by targeting content or advertisements to the user at a later time.
A disadvantage to using profiling to target advertisements is that there are inherent latencies in the time it takes to build up each user's profile. Such behavior profiling often uses data-mining techniques to determine trend information from ad server log files. Such data-mining techniques are then used to model behaviors of each targeted audience. Behavior modeling, however, has inherent latencies in predicting a new user behavior from the time the user first exhibits such behavior, which can take days to link an appropriate advertisement to a new consumer behavior. Hence, advertisements linked to behavior modeled features will not have an optimum exposure to the targeted audience.
A further conventional approach is advertisement queuing, where a fixed number of advertisements are each queued to display on subsequently presented web pages. In keyword advertising applications, this approach allows advertisers to present their advertisements to users subsequent to the presentation of a search results page and a corresponding keyword advertisement. A drawback to this approach, however, is that such queued advertisements are generally run of the network ads and are of no, or very low, interest to the particular user performing the search.
Therefore, there is need for a system and method for presenting advertisements to targeted users who are interested in such product or service information nearly immediately following the presented results of a keyword search. Such a system and method decreases the latency between the time that the user exhibits some behavior on the web site and the time that an advertiser capitalizes on that behavior for ad-targeting. Furthermore, there is a need to capture ad revenue that otherwise would be lost using conventional ad-targeting techniques by presenting a targeted advertisement to a unique user.